Abstract/Description

The analogues approach, developed by CCAFS in R programming, is a novel way of supporting
climate and crop models with on-the-ground empirical testing. In essence, the analogues tool
connects sites with statistically similar (‘analogous’) climates, across space (i.e. between
locations) and/or time (i.e. with past or future climates). A CCAFS dissimilarity index or
Hallegatte index can be used to systematically identify climate analogues across the world, for
certain regions, or among specific locations. Users may use default criteria or choose from a
variety of global climate models (GCMs), scenarios, and input data. Once analogue sites are
identified, information gathered from local field studies or databases can be used and compared
to provide data for further studies, propose high-potential adaptation pathways, facilitate
farmer-to-farmer exchange of knowledge, validate computational models, test new technologies
and/or techniques, or enable us to learn from history. Users may manipulate the tool in the free,
open-source R software, or access a simplified user-friendly version online.